(Christopher Brown has been working as a DevSecOps engineer in an IT company that develops software and web applications for an ecommerce company. To automatically detect common security issues and coding error in the C++ code, she performed code scanning using CodeQL in GitHub. Which of the following entries will Christopher find for CodeQL analysis of C++ code?)
Answer(s): D
When GitHub Code Scanning is enabled using CodeQL, each supported programming language is identified by a specific language key. For C++ code, CodeQL uses the identifier cpp, not "cp." CodeQL workflows are commonly configured to run during pull request events so that security issues and coding errors can be detected and reviewed before code is merged into the main branch. As a result, the CodeQL analysis entry displayed in GitHub Actions and the Security tab for C++ pull request analysis appears as CodeQL/Analyze (cpp) (pull-request). Options A and B are incorrect because "cp" is not a valid CodeQL language identifier. Option C uses the correct language identifier but references an incorrect event format. Identifying the correct CodeQL analysis entry helps DevSecOps engineers confirm that scans are executing correctly for the intended language during the Code stage and that security feedback is available early in the development lifecycle.
(Evan Peters has been working as a DevSecOps engineer in an IT company located in Denver,Colorado. His organization has deployed various applications on Docker containers. Evan has been running SSH service inside the containers, and handling of SSH keys and access policies is a major security concern for him. What will be the solution for Evan security concern?)
Running an SSH service inside Docker containers is considered a security anti-pattern because it increases the attack surface and complicates key and access management. Containers are designed to run a single primary process and be managed externally rather than accessed via SSH. The recommended solution is to run SSH on the host system and use docker exec to interact with containers when administrative access is required. This approach eliminates the need to manage SSH keys inside containers, reduces exposure to brute-force attacks, and simplifies access control. The other options incorrectly suggest running SSH in inappropriate locations such as the registry, client, or build process, which do not address the core security concern. During the Operate and Monitor stage, minimizing unnecessary services within containers is critical to enforcing least privilege and maintaining a secure runtime environment.
(Craig Kelly has been working as a software development team leader in an IT company over the past 8 years. His team is working on the development of an Android application product. Sandra Oliver, a DevSecOps engineer, used DAST tools and fuzz testing to perform advanced checks on the Android application product and detected critical and high severity issues. She provided the information about the security issues and the recommendations to mitigate them to Craig's team. Which type of security checks performed by Sandra involve detection of critical and high severity issues using DAST tools and fuzz testing?)
Dynamic Application Security Testing (DAST) and fuzz testing require a running application in order to actively probe for vulnerabilities such as injection flaws, authentication bypasses, and improper input handling. These techniques are therefore performed after the application has been built and deployed to a testing environment, categorizing them as test-time checks. Commit-time and build- time checks rely primarily on static analysis and dependency scanning and do not exercise application behavior at runtime. Deploy-time checks focus on configuration validation rather than aggressive attack simulation. Test-time checks are specifically designed to uncover critical and high- severity vulnerabilities by mimicking real-world attack scenarios. Performing DAST and fuzz testing during this stage allows teams to detect exploitable flaws before production release, significantly strengthening application security.
(SinCaire is a software development company that develops web applications for various clients. To measure the successful implementation of DevSecOps, the organization enforced U.S. General Service Administrator (GSA) high-value DevSecOps metrics. Which of the following metrics implemented by SinCaire can measure the time between the code commit and production, and tracks the bug fix and new features throughout the development, testing, and production phases?)
Change lead time measures the duration between a code commit and its successful deployment into production. This metric tracks how efficiently new features, bug fixes, and changes move through development, testing, and release stages. It is a key DevSecOps performance indicator used to assess pipeline efficiency and the effectiveness of automation and security integration. Mean time to recovery focuses on restoring service after incidents, change volume measures the number of changes rather than delivery speed, and time to value is a broader business metric. Change lead time directly reflects how well DevSecOps practices enable rapid yet secure delivery, making it the correct metric for measuring commit-to-production flow across all phases.
(Dustin Hoffman has been working as a DevSecOps engineer in an IT company located in San Diego, California. For detecting new security vulnerabilities at the beginning of the source code development, he would like to integrate Checkmarx SCA tool with GitLab. The Checkmarx template has all the jobs defined for pipeline. Where should Dustin incorporate the Checkmarx template file `https://raw.githubusercontent.com/checkmarx-ltd/cx-flow/develop/templates/gitlab/v3/Checkmarx.gitlab-ci.yml'?)
GitLab CI/CD pipelines are defined using a configuration file named gitlab-ci.yml, which must be placed in the root directory of the repository. This file controls pipeline stages, jobs, and template inclusions. To integrate Checkmarx SCA using a predefined template, the template reference must be included in the root-level gitlab-ci.yml file so GitLab can load and execute the defined jobs automatically. The other filenames listed in the options are not recognized by GitLab as valid pipeline configuration files. Integrating SCA at the Code stage allows early detection of vulnerable open- source dependencies, reducing remediation cost and preventing insecure components from progressing further in the DevSecOps pipeline.
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